CN110600075A - Protein ATP docking method based on ligand growth strategy - Google Patents
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Abstract
A protein ATP docking method based on a ligand growth strategy comprises the steps of firstly, predicting protein ATP binding residue information by using an ATPbind server, and assisting in docking protein and small molecules; then, the ligand is decomposed into a plurality of fragments to be sequentially butted, and the spatial positions of the fragments are optimized by using an energy function, so that the prediction precision of the protein-ATP compound structure is improved; finally, the optimal space conformation of each ligand fragment is rapidly searched by using a simulated annealing algorithm, so that the calculation efficiency is improved. The invention provides a protein-ATP docking method based on a ligand growth strategy, which has high calculation speed and high prediction accuracy.
Description
Technical Field
The invention relates to the fields of bioinformatics, intelligent optimization and computer application, in particular to a protein ATP docking method based on a ligand growth strategy.
Background
The function of many proteins depends on their interaction with small molecules or ligands, ATP being one of the important ligands, and playing a key role in the prediction of protein structural function. ATP is an important energy molecule and coenzyme in the field of molecular biology, and ATP and protein binding play an important role in intracellular transport, muscle contraction, cell movement, and regulation of various metabolic processes. The goal of studying protein-ligand docking is to better understand the protein-ligand interaction by knowing the three-dimensional structure of the ligand and the protein of interest, using computational means to predict and evaluate the three-dimensional conformation of the protein-ligand complex. Protein-ligand docking is also increasingly realistic and reliable as the number and computational power of resolved protein monomer structures continues to increase.
The protein-ligand docking problem can be generally described as: given the monomeric three-dimensional structure of small molecule ligands and target proteins, the three-dimensional conformation of the protein-ligand complex is predicted and evaluated by placement of the ligand at the binding site of the protein. Protein-ligand docking problems can be further divided into rigid docking and flexible docking depending on whether the flexibility of the ligand and receptor is considered during docking. Rigid docking, as the name implies, refers to docking in which proteins and small molecules act as rigid objects without changing their spatial shape during docking. In the early protein-protein docking or protein-small molecule ligand docking algorithm, the target protein is mostly simplified and processed into rigid molecules, obviously, the rigid simplification process may cause great deviation of a prediction result, and obviously, rigid docking cannot well obtain an accurate spatial structure of the compound. Flexible docking can be further classified into flexible ligand docking and flexible receptor docking. Flexible ligand docking refers to treating a ligand as a flexible molecule; while flexible receptor docking treats both ligand and receptor macromolecular proteins as flexible molecules. During the flexible docking process, the ligand and the protein may have changes in spatial positions such as bond length, bond angle, dihedral angle, etc. Although the prediction accuracy of the existing flexible docking method is higher than that of the rigid docking method, the time consumption of the docking process is too long, and the requirement of rapidly completing docking of a large amount of proteins and ligands cannot be met.
Therefore, the existing protein and ligand molecule docking methods have defects in computational efficiency and prediction accuracy, and need to be improved.
Disclosure of Invention
In order to overcome the defects of the existing protein and ATP docking method in the aspects of calculation efficiency and prediction accuracy, the invention provides a ligand growth strategy-based protein ATP docking method with high calculation speed and high prediction accuracy.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a method of protein ATP docking based on a ligand growth strategy, the method comprising the steps of:
1) inputting structural information of protein and ATP, and respectively marking as R and A;
2) for the input structure information R, the residue information bound by the protein-ATP is predicted by using an ATPbind server (https:// zhangglab. ccmb. med. umich. edu/ATPbind /), and n residues bound by the protein and the ATP are obtained and are respectively marked as R1,r2,...,rn；
3) According to r1,r2,...,rnCentral carbon atom C ofαCoordinate information, take all CαClustering a central point C by the average value of the coordinate valuesRAccording to the information of each atomic coordinate in A, taking the average value of all atomic coordinate values to cluster a central point CAMoving A so that CAAnd CRThe coordinates of the two points coincide;
4) for each ATP molecule in the PDB database(j)N, N is the number of ATP in the PDB database, for each atom of each ATPN, where n is the number of atoms in ATP, and calculatingC of binding residue to T-type proteinαDistance between atomsWherein T is one of the types of amino acid residues present in PDB;
5) calculating C of binding residue of kth atom of ATP and T type protein in PDB databaseαThe average distance of atomic interactions, denoted DkT：
Wherein
6) Dividing all atoms in A into M groups of small molecules in a single bond form, wherein the spatial position of the first group of small molecules is unchanged, the small molecules of other groups are randomly distributed in space, each group of small molecules is provided with X atoms, and the coordinate of each atom is Cmx，m＝1,2,...,M，x＝1,2,...,X；
7) Carrying out the following process on X atoms of each group of small molecules, and setting m to be 1;
8) setting parameters: setting population size NP, initial temperature TcTemperature lowering rate t0；
9) Population initialization: randomly generating an initialization population P ═ S1,S2,...,Si,...,SNP}，Si＝(si,1,si,2,si,3) Is the i-th individual of the population P, where si,1、si,2And si,3The value range of (a) is 0 to 2 pi;
10) according to a simulated annealing algorithm, for each individual S in the population PiI ∈ {1,2, …, NP }, proteins were docked with each set of small molecules, assuming i ═ 1:
10.1) when m is 1, jumping to step 10.2); otherwise, the set of small molecules is subjected to flatteningShifting to make the first atom of the group form a single bond with the last atom of the previous group, and updating the coordinates of the atoms of the group after the shift to Cm1，Cm2，…，CmX；
10.2) according to SiThree elements of (1) si,1、si,2And si,3Calculating a three-dimensional space rotation matrix R:
10.3) mixing Cm1，Cm2，…，CmXThe coordinates are rotated according to the rotation matrix R to respectively obtain three-dimensional coordinates
10.4) according to step 5), calculate the score (S)i)：
Wherein DmxTIs thatC binding residues to type TaThe distance of atoms, X ═ 1, 2., X, k areNumber of atoms in ATP;
10.5) when i > 1, if score (S)i)＜score(Si-1) Receiving the structural information of the group of small molecules; otherwise, calculating the acceptance probability p, generating a random number Q between (0,1), and accepting the structural information of the group of small molecules at the moment if p > Q, wherein
10.6)i＝i+1，Tc＝t0*Tc(ii) a If i is less than or equal to NP, skipping to the step 10.1); otherwise, outputting the position information of all the atom coordinates of the group of small molecules;
11) if M is equal to M +1, if M is less than or equal to M, jumping to the step 8); otherwise, outputting the atomic coordinates of the M groups as final ATP position information.
The technical conception of the invention is as follows: firstly, predicting protein ATP binding residue information by using an ATPbind server, and assisting the docking of protein and small molecules; then, the ligand is decomposed into a plurality of fragments to be sequentially butted, and the spatial positions of the fragments are optimized by using an energy function, so that the prediction precision of the protein-ATP compound structure is improved; finally, the optimal space conformation of each ligand fragment is rapidly searched by using a simulated annealing algorithm, so that the calculation efficiency is improved. The invention provides a protein-ATP docking method based on a ligand growth strategy, which has high calculation speed and high prediction accuracy.
The beneficial effects of the invention are as follows: on one hand, the ATPbind server is used for predicting protein-ATP binding residue information and ligand decomposition heavy docking, so that the prediction precision of the molecular space structure of the protein-ATP compound is improved; on the other hand, the optimal fragment conformation of the ligand is searched by using a simulated annealing algorithm, so that the efficiency of protein-ATP docking prediction is improved.
Drawings
FIG. 1 is a schematic diagram of a protein ATP docking method based on a ligand growth strategy.
FIG. 2 is a three-dimensional space structure diagram of a complex predicted by protein 1g64 and ATP using a protein ATP docking method based on ligand growth strategy.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Referring to fig. 1 and 2, a protein to ATP docking method based on a ligand growth strategy includes the following steps:
1) inputting structural information of protein and ATP, and respectively marking as R and A;
2) for the input structural information R, ATPbind Server (https:// zhangl) is usedab. ccmb. med. umich. edu/ATPbind /) predicts the protein-ATP bound residue information, obtains n residues bound by the protein and ATP, and respectively records as r1,r2,...,rn；
3) According to r1,r2,...,rnCentral carbon atom C ofαCoordinate information, take all CαClustering a central point C by the average value of the coordinate valuesRAccording to the information of each atomic coordinate in A, taking the average value of all atomic coordinate values to cluster a central point CAMoving A so that CAAnd CRThe coordinates of the two points coincide;
4) for each ATP molecule in the PDB database(j)N, N is the number of ATP in the PDB database, for each atom of each ATPN, where n is the number of atoms in ATP, and calculatingC of binding residue to T-type proteinαDistance between atomsWherein T is one of the types of amino acid residues present in PDB;
5) calculating C of binding residue of kth atom of ATP and T type protein in PDB databaseαThe average distance of atomic interactions, denoted DkT：
Wherein
6) Dividing all atoms in A into M groups of small molecules in single bond form, wherein the spatial position of the first group of small molecules is unchanged, and the other groups of small moleculesThe small molecules are randomly distributed in space, each group of small molecules is provided with X atoms, and each atom coordinate is Cmx，m＝1,2,...,M，x＝1,2,...,X；
7) Carrying out the following process on X atoms of each group of small molecules, and setting m to be 1;
8) setting parameters: setting population size NP, initial temperature TcTemperature lowering rate t0；
9) Population initialization: randomly generating an initialization population P ═ S1,S2,...,Si,...,SNP}，Si＝(si,1,si,2,si,3) Is the i-th individual of the population P, where si,1、si,2And si,3The value range of (a) is 0 to 2 pi;
10) according to a simulated annealing algorithm, for each individual S in the population PiI ∈ {1,2, …, NP }, proteins were docked with each set of small molecules, assuming i ═ 1:
10.1) when m is 1, jumping to step 10.2); otherwise, translating the group of small molecules to enable the first atom of the group to form a single bond with the last atom of the previous group, and respectively updating the coordinates of the atoms of the group after translation to Cm1，Cm2，…，CmX；
10.2) according to SiThree elements of (1) si,1、si,2And si,3Calculating a three-dimensional space rotation matrix R:
10.3) mixing Cm1，Cm2，…，CmXThe coordinates are rotated according to the rotation matrix R to respectively obtain three-dimensional coordinates
10.4) according to step 5), calculate the score (S)i)：
Wherein DmxTIs thatC binding residues to type TaThe distance of atoms, X ═ 1, 2., X, k areNumber of atoms in ATP;
10.5) when i > 1, if score (S)i)＜score(Si-1) Receiving the structural information of the group of small molecules; otherwise, calculating the acceptance probability p, generating a random number Q between (0,1), and accepting the structural information of the group of small molecules at the moment if p > Q, wherein
10.6)i＝i+1，Tc＝t0*Tc(ii) a If i is less than or equal to NP, skipping to the step 10.1); otherwise, outputting the position information of all the atom coordinates of the group of small molecules;
11) if M is equal to M +1, if M is less than or equal to M, jumping to the step 8); otherwise, outputting the atomic coordinates of the M groups as final ATP position information.
In this embodiment, taking the three-dimensional space structure of the complex after predicting the docking of protein 1g64 and ATP as an example, a protein ATP docking method based on a ligand growth strategy comprises the following steps:
1) inputting structural information of protein and ATP, and respectively marking as R and A;
2) for the input structure information R, the residue information bound by the protein-ATP is predicted by using an ATPbind server (https:// zhangglab. ccmb. med. umich. edu/ATPbind /), and n residues bound by the protein and the ATP are obtained and are respectively marked as R1,r2,...,rn；
3) According to r1,r2,...,rnCentral carbon atom C ofαCoordinate information, take all CαClustering a central point C by the average value of the coordinate valuesRAccording to the information of each atomic coordinate in A, taking the average value of all atomic coordinate values to cluster a central point CAMoving A so that CAAnd CRThe coordinates of the two points coincide;
4) for each ATP molecule in the PDB database(j)N, N is the number of ATP in the PDB database, for each atom of each ATPN, where n is the number of atoms in ATP, and calculatingC of binding residue to T-type proteinαDistance between atomsWherein T is one of the types of amino acid residues present in PDB;
5) calculating C of binding residue of kth atom of ATP and T type protein in PDB databaseαThe average distance of atomic interactions, denoted DkT：
Wherein
6) Dividing all atoms in A into M groups of small molecules in a single bond form, wherein the spatial position of the first group of small molecules is unchanged, the small molecules of other groups are randomly distributed in space, each group of small molecules is provided with X atoms, and the coordinate of each atom is Cmx，m＝1,2,...,M，x＝1,2,...,X；
7) Carrying out the following process on X atoms of each group of small molecules, and setting m to be 1;
8) setting parameters: setting population size NP100, initial temperature TcCooling rate t 1000 ═ t0＝0.98；
9) Population initialization: randomly generating an initialization population P ═ S1,S2,...,Si,...,SNP}，Si＝(si,1,si,2,si,3) Is the i-th individual of the population P, where si,1、si,2And si,3The value range of (a) is 0 to 2 pi;
10) according to a simulated annealing algorithm, for each individual S in the population PiI ∈ {1,2, …, NP }, proteins were docked with each set of small molecules, assuming i ═ 1:
10.1) when m is 1, jumping to step 10.2); otherwise, translating the group of small molecules to enable the first atom of the group to form a single bond with the last atom of the previous group, and respectively updating the coordinates of the atoms of the group after translation to Cm1，Cm2，…，CmX；
10.2) according to SiThree elements of (1) si,1、si,2And si,3Calculating a three-dimensional space rotation matrix R:
10.3) mixing Cm1，Cm2，…，CmXThe coordinates are rotated according to the rotation matrix R to respectively obtain three-dimensional coordinates
10.4) according to step 5), calculate the score (S)i)：
Wherein DmxTIs thatC binding residues to type TaDistance of atoms, x ═ 12, 1, X, k isNumber of atoms in ATP;
10.5) when i > 1, if score (S)i)＜score(Si-1) Receiving the structural information of the group of small molecules; otherwise, calculating the acceptance probability p, generating a random number Q between (0,1), and accepting the structural information of the group of small molecules at the moment if p > Q, wherein
10.6)i＝i+1，Tc＝t0*Tc(ii) a If i is less than or equal to NP, skipping to the step 10.1); otherwise, outputting the position information of all the atom coordinates of the group of small molecules;
11) if M is equal to M +1, if M is less than or equal to M, jumping to the step 8); otherwise, outputting the atomic coordinates of the M groups as final ATP position information.
Using the three-dimensional space structure of the protein 1g64 and ATP as an example, the root mean square deviation of the three-dimensional space structure information of the protein 1g64 and ATP obtained by the above method from the structure of the complex measured by a wet experiment isThe predicted protein ATP complex structure is shown in figure 2.
The above description is the prediction result of the present invention using protein 1g64 and ATP as examples, and is not intended to limit the scope of the present invention, and various modifications and improvements can be made without departing from the scope of the present invention.
Claims (1)
1. A protein ATP docking method based on a ligand growth strategy is characterized in that: the butt joint method comprises the following steps:
1) inputting structural information of protein and ATP, and respectively marking as R and A;
2) for the input structure information R, predicting the residue information bound by the protein-ATP by using an ATPbind server to obtain n residues bound by the protein and the ATP, and respectively marking the n residues as R1,r2,...,rn；
3) According to r1,r2,...,rnCentral carbon atom C ofαCoordinate information, take all CαClustering a central point C by the average value of the coordinate valuesRAccording to the information of each atomic coordinate in A, taking the average value of all atomic coordinate values to cluster a central point CAMoving A so that CAAnd CRThe coordinates of the two points coincide;
4) for each ATP molecule in the PDB database(j)N, N is the number of ATP in the PDB database, for each atom of each ATPWherein n is the number of atoms in ATP, and calculatingC of binding residue to T-type proteinαDistance between atomsWherein T is one of the types of amino acid residues present in PDB;
5) calculating C of binding residue of kth atom of ATP and T type protein in PDB databaseαThe average distance of atomic interactions, denoted DkT：
Wherein
6) Dividing all atoms in A into single bondsForming M groups of small molecules, wherein the spatial position of the first group of small molecules is unchanged, the small molecules of other groups are randomly distributed in space, each group of small molecules is provided with X atoms, and the coordinate of each atom is Cmx，m＝1,2,...,M，x＝1,2,...,X；
7) Carrying out the following process on X atoms of each group of small molecules, and setting m to be 1;
8) setting parameters: setting population size NP, initial temperature TcTemperature lowering rate t0；
9) Population initialization: randomly generating an initialization population P ═ S1,S2,...,Si,...,SNP}，Si＝(si,1,si,2,si,3) Is the i-th individual of the population P, where si,1、si,2And si,3The value range of (a) is 0 to 2 pi;
10) according to a simulated annealing algorithm, for each individual S in the population PiI ∈ {1,2, …, NP }, proteins were docked with each set of small molecules, assuming i ═ 1:
10.1) when m is 1, jumping to step 10.2); otherwise, translating the group of small molecules to enable the first atom of the group to form a single bond with the last atom of the previous group, and respectively updating the coordinates of the atoms of the group after translation to Cm1，Cm2，…，CmX；
10.2) according to SiThree elements of (1) si,1、si,2And si,3Calculating a three-dimensional space rotation matrix R:
10.3) mixing Cm1，Cm2，…，CmXThe coordinates are rotated according to the rotation matrix R to respectively obtain three-dimensional coordinates
10.4) according to step 5), calculate the score (S)i)：
Wherein DmxTIs thatC binding residues to type TaThe distance of atoms, X ═ 1, 2., X, k areNumber of atoms in ATP;
10.5) when i > 1, if score (S)i)＜score(Si-1) Receiving the structural information of the group of small molecules; otherwise, calculating the acceptance probability p, generating a random number Q between (0,1), and accepting the structural information of the group of small molecules at the moment if p > Q, wherein
10.6)i＝i+1，Tc＝t0*Tc(ii) a If i is less than or equal to NP, skipping to the step 10.1); otherwise, outputting the position information of all the atom coordinates of the group of small molecules;
11) if M is equal to M +1, if M is less than or equal to M, jumping to the step 8); otherwise, outputting the atomic coordinates of the M groups as final ATP position information.
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